Technologies for determining a threat assessment based on fear responses

ABSTRACT

Technologies for determining a threat assessment based on fear responses comprises monitoring sensor data received from a sensor array located at a monitored site. The sensor data may include behavioral sensor data indicative of a physical behavior of individuals within the monitored site and physiological sensor data indicative of physiological characteristics of individuals within the monitored site. The threat assessment may be based on the behavioral sensor data and physiological sensor data. In some embodiments, context data related to the monitored site may be utilized analyze the behavioral sensor data and physiological sensor data and determine a threat assessment based thereon.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation application of U.S.application Ser. No. 14/583,695, entitled “TECHNOLOGIES FOR DETERMININGA THREAT ASSESSMENT BASED ON FEAR RESPONSES,” which was filed on Dec.27, 2014.

BACKGROUND

Due to the increasing size of public events, the increasing mobility ofthe common person, and other factors, it is becoming more difficult todetect public security events or threats. Although some locations areheavily monitored with multiple threat detection systems, oftentimes themultiple threat detection systems are unconnected from each other orotherwise not in direct communication. Additionally, other locations mayhave smaller or no threat detection systems in place.

Many typical threat detection systems are reactionary systems thatdepend upon an exposed or current threat (e.g., after the threat hasrealized) or based on past behavior of specifically monitoredindividuals (e.g., purchasing patterns, online activity, etc.). In thisway, a typical threat detection system measures static behavior, oftenfocused on a single person or small group of identified people. As such,typical threat detection and security systems are unable to predict orinfer a threat condition based on real-time data.

BRIEF DESCRIPTION OF THE DRAWINGS

The concepts described herein are illustrated by way of example and notby way of limitation in the accompanying figures. For simplicity andclarity of illustration, elements illustrated in the figures are notnecessarily drawn to scale. Where considered appropriate, referencelabels have been repeated among the figures to indicate corresponding oranalogous elements.

FIG. 1 is a simplified block diagram of at least one embodiment of asystem for determining a threat assessment based on fear responses ofmonitored individuals;

FIG. 2 is a simplified block diagram of at least one embodiment of anenvironment that may be established by a threat monitoring system of thesystem of FIG. 1;

FIG. 3 is a simplified block diagram of at least one embodiment ofvarious environments that may be established by devices of the system ofFIG. 1; and

FIG. 4 is a simplified block diagram of at least one method fordetermining a threat assessment that may be executed by the threatmonitoring system of FIGS. 1-3.

DETAILED DESCRIPTION OF THE DRAWINGS

While the concepts of the present disclosure are susceptible to variousmodifications and alternative forms, specific embodiments thereof havebeen shown by way of example in the drawings and will be describedherein in detail. It should be understood, however, that there is nointent to limit the concepts of the present disclosure to the particularforms disclosed, but on the contrary, the intention is to cover allmodifications, equivalents, and alternatives consistent with the presentdisclosure and the appended claims.

References in the specification to “one embodiment,” “an embodiment,”“an illustrative embodiment,” etc., indicate that the embodimentdescribed may include a particular feature, structure, orcharacteristic, but every embodiment may or may not necessarily includethat particular feature, structure, or characteristic. Moreover, suchphrases are not necessarily referring to the same embodiment. Further,when a particular feature, structure, or characteristic is described inconnection with an embodiment, it is submitted that it is within theknowledge of one skilled in the art to effect such feature, structure,or characteristic in connection with other embodiments whether or notexplicitly described. Additionally, it should be appreciated that itemsincluded in a list in the form of “at least one A, B, and C” can mean(A); (B); (C): (A and B); (B and C); (A and C); or (A, B, and C).Similarly, items listed in the form of “at least one of A, B, or C” canmean (A); (B); (C): (A and B); (B and C); (A or C); or (A, B, and C).

The disclosed embodiments may be implemented, in some cases, inhardware, firmware, software, or any combination thereof. The disclosedembodiments may also be implemented as instructions carried by or storedon one or more transitory or non-transitory machine-readable (e.g.,computer-readable) storage medium, which may be read and executed by oneor more processors. A machine-readable storage medium may be embodied asany storage device, mechanism, or other physical structure for storingor transmitting information in a form readable by a machine (e.g., avolatile or non-volatile memory, a media disc, or other media device).

In the drawings, some structural or method features may be shown inspecific arrangements and/or orderings. However, it should beappreciated that such specific arrangements and/or orderings may not berequired. Rather, in some embodiments, such features may be arranged ina different manner and/or order than shown in the illustrative figures.Additionally, the inclusion of a structural or method feature in aparticular figure is not meant to imply that such feature is required inall embodiments and, in some embodiments, may not be included or may becombined with other features.

Referring now to FIG. 1, a system 100 for determining a threatassessment at a monitored site includes a threat monitoring system 102and one or more sensor arrays 104 located at the monitored site. Asdiscussed in more detail below, the threat monitoring system 102 isconfigured to determine a threat assessment for a monitored site basedon an analysis of sensor data indicative of fear responses ofindividuals located at the monitored site. To do so, the threatmonitoring system 102 analyzes sensor data generated by one or moresensors 150 of the sensor array 104. As discussed in more detail below,the sensors 150 may be embodied as a diverse collection of sensorsincluding permanent security sensors, personal or company monitoringsensors, individual sensors, and/or other sensors located at themonitored location. The sensor data generated by the sensor array 104may include any type of data useful to the threat monitoring system 102in determining the presence of a threat. For example, the sensor datamay include behavioral sensor data, which may be indicative of fearresponses of individuals at a monitored site, and physiological sensordata, which may be indicative of actual fear felt by the individuals atthe monitored site.

To determine a threat assessment of a monitored location, the threatmonitoring system 102 analyzes the behavior sensor data to determine thephysical behaviors of individuals located at the monitored site (e.g.,are the individuals running away from a common location) and thephysiological sensor data to determine physiological characteristics ofthe individuals located at the monitored site (e.g., increase heartrate, sweating, release of adrenalin, galvanic skin response, etc.). Inthis way, the threat monitoring system 102 monitors for abnormalbehavior and physiological responses to determine the possibility of athreat. Of course, some typically abnormal behavior may be normal undersome conditions. For example, while a group of people running in unisonmay be suspicious with no context, such a behavior may be expected ifthe group is headed toward a public transit about to leave the station.As such, to improve the accuracy of the threat assessment, the threatmonitoring system 102 also retrieves or determines context data relatedto the monitored site and adjusts the analysis of the behavior sensordata and physiological sensor data based on the associated context data.As discussed in more detail below, the context data may be embodied asany type of data that may provide insight or explanation of behaviorsand response of individuals located at the monitored site (e.g.,cultural context, temporal context, etc.). To obtain the context data,the threat monitoring system 102 may access one or more informationsystems 106 over a network 110. As discussed in more detail below, theinformation systems 106 may be embodied as any type of source fromcontext information may be obtained.

If the threat monitoring system 102 determines, based on the sensordata, that a threat is occurring or likely occurring, the threatmonitoring system 102 may activate one or more threat response systems108. The threat response systems 108 may be embodied as any type ofsystem useful in responding to the threat, such as emergency responsesystems, as discussed in more detail below.

The threat monitoring system 102 may be embodied as any type of computersystem capable of determining a threat assessment based on the sensordata from the sensor array 104 and performing the other functionsdescribed herein. For example, the threat monitoring system 102 may beembodied as a server, a computer, a multiprocessor system, aprocessor-based system, a desktop computer, a tablet computer, anotebook computer, a laptop computer, or any other computing devicecapable of generating a threat assessment as described herein. Althoughthe threat monitoring system 102 is illustratively shown in FIG. 1 assingle computing device, it should be appreciated that the threatmonitoring system 102 may be embodied as a distributed computing system,a virtual computing system, a cloud service, a collection of computersor computing systems, or otherwise have a distributed architecture.

As shown in FIG. 1, the threat monitoring system 102 includes aprocessor 120, an I/O subsystem 122, a memory 124, a data storage 126,and a communication circuit 128. Of course, the threat monitoring system102 may include other or additional components, such as those commonlyfound in a computer (e.g., various input/output devices), in otherembodiments. Additionally, in some embodiments, one or more of theillustrative components may be incorporated in, or otherwise form aportion of, another component. For example, the memory 124, or portionsthereof, may be incorporated in the processor 120 in some embodiments

The processor 120 may be embodied as any type of processor capable ofperforming the functions described herein. For example, the processor120 may be embodied as a single or multi-core processor(s), a single ormulti-socket processor, a digital signal processor, a microcontroller,or other processor or processing/controlling circuit. Similarly, thememory 124 may be embodied as any type of volatile or non-volatilememory or data storage capable of performing the functions describedherein. In operation, the memory 124 may store various data and softwareused during operation of the threat monitoring system 102 such asoperating systems, applications, programs, libraries, and drivers. Thememory 124 is communicatively coupled to the processor 120 via the I/Osubsystem 122, which may be embodied as circuitry and/or components tofacilitate input/output operations with the processor 120, the memory124, and other components of the threat monitoring system 102. Forexample, the I/O subsystem 122 may be embodied as, or otherwise include,memory controller hubs, input/output control hubs, firmware devices,communication links (i.e., point-to-point links, bus links, wires,cables, light guides, printed circuit board traces, etc.) and/or othercomponents and subsystems to facilitate the input/output operations. Insome embodiments, the I/O subsystem 122 may form a portion of asystem-on-a-chip (SoC) and be incorporated, along with the processor120, the memory 124, and other components of the threat monitoringsystem 102, on a single integrated circuit chip.

The data storage 126 may be embodied as any type of device or devicesconfigured for the short-term or long-term storage of data. For example,the data storage 126 may include any one or more memory devices andcircuits, memory cards, hard disk drives, solid-state drives, or otherdata storage devices.

The communication circuit 128 may be embodied as any communicationcircuit, device, or collection thereof, capable of enablingcommunications between the threat monitoring system 102 and theinformation systems 106 and threat response systems 108. To do so, thecommunication circuit 128 may be configured to use any one or morecommunication technology and associated protocols (e.g., Ethernet,Bluetooth®, Wi-Fi®, WiMAX, etc.) to effect such communication.

In some embodiments, the threat monitoring system 102 may furtherinclude one or more peripheral devices 130. Such peripheral devices 130may include any type of peripheral device commonly found in a server orcomputer device, for example, a hardware keyboard, input/output devices,peripheral communication devices, and/or other peripheral devices.

The sensor array 104 may include any number of individual sensors 150.As discussed above, some of the sensors 150 may be pre-establishedthreat assessment sensors such as stationary or mobile cameras, motionsensors, chemical sensors, or the like. Additionally, some of thesensors 150 may be “commandeered” sensors of a third-party. For example,the threat monitoring system 102 may utilize a camera located at aretail establishment located within the monitored site, a glass breakagesensor located at a bank within the monitored site, a traffic sensor,vehicle cameras and sensors, communication sensors, and/or the like.Further, some of the sensors 150 may be personal sensors carried byindividuals located within the monitored site. For example, the sensors150 may be embodied as, or otherwise include, head-mounted cameras,smart glasses, biometric sensors, heart-rate sensors, audio sensor,motion sensor, proximity sensor, pedometer, breathing sensors, or anyother sensor capable of generating physiological or behavioral sensordata of the wearer. Of course, due to privacy concerns, the sharing ofsuch personal data to the threat monitoring system 102 may opted into oranonymized. It should be appreciated that the sensor array 104 mayinclude any number of sensors 150. Additionally, the collection ofsensors 150 defining the sensor array 104 may change over time assensors become available or are removed from the monitored site.

Each information system 106 may be embodied as any type of computerinformation system with which the threat monitoring system 102 maycommunicate to determine context data about the monitored site. Forexample, if the monitored site is a subway station, the threatmonitoring system 102 may communicate with an information system havingthe schedule of subway comings and goings.

Similarly, the threat response systems 108 may be embodied as any typeof system, collection of devices, services, entities, or other resourceswhich the threat monitoring system 102 may employ to respond to ormitigate a perceived threat. For example, the threat response systems108 may include emergency responders (police, firemen, and medicalpersonnel), traffic control systems, public notification or addresssystems, and/or other services, systems, or devices useful in respondingto a threat.

As discussed above, the threat monitoring system 102 may communicatewith the information systems 106 and the threat response systems 108over the network 110. The network 110 may be embodied as any type ofcommunication network capable of facilitating such communication. Assuch, the network 110 may include one or more networks, routers,switches, computers, and/or other intervening devices. For example, thenetwork 110 may be embodied as or otherwise include one or more local orwide area networks, cellular networks, publicly available globalnetworks (e.g., the Internet), an ad hoc network, a short-rangecommunication network or link, or any combination thereof.

Referring now to FIG. 2, in use the threat monitoring system 102 mayestablish an environment 200. The illustrative environment 200 includesa sensor management module 202, a behavioral analysis module 204, aphysiological analysis module 206, a context analysis module 208, and athreat assessment module 210. Each of the modules and other componentsof the environment 200 may be embodied as firmware, software, hardware,or a combination thereof. For example the various modules, logic, andother components of the environment 200 may form a portion of, orotherwise be established by, the processor 120, the I/O subsystem 122,an SoC, or other hardware components of the threat monitoring system102′. As such, in some embodiments, any one or more of the modules ofthe environment 200 may be embodied as a circuit or collection ofelectrical devices (e.g., a sensor management circuit, a behavioralanalysis circuit, a physiological analysis circuit, a context analysiscircuit, and a threat assessment circuit, etc.).

The sensor management module 202 is configured to obtain sensor datafrom the sensor array 104. To do so, in some embodiments, the sensormanagement module 202 may select sensors 150 for inclusion in the sensorarray 104 and communicate with those sensors 150 to obtain the relevantsensor data. For example, in embodiments in which individuals within themonitored site are wearing personal sensors 150, the sensor managementmodule 202 may establish a connection with those personal sensors 150 orotherwise retrieve sensor data from the personal sensors 150. In someembodiments, the sensor management module 202 may differentiate thesensor data. For example, the sensor management module 202 may providebehavioral sensor data to the behavioral analysis module 204 andphysiological sensor data to the physiological analysis module 206.

The behavioral analysis module 204 is configured to analyze behavioraldata from the sensor data received from the sensor array 104. In theillustrative embodiment, the behavioral analysis module 204 analyzes thebehavioral data indicative of physical behavior of individuals in themonitored site. For example, the behavioral analysis module 204 maymonitor the behavioral sensor data to identify abnormal physicalbehavior. To do so, the behavioral analysis module 204 may compare thephysical behavior of monitored individuals to the physical behavior ofother individuals at the monitored location and/or expected physicalbehavior. For example, the behavioral analysis module 204 may identifyindividuals moving against the flow of a crowd, individuals wearingabnormal clothing, individuals in a crowd giving wide breadth to aspecific individual, herd-like crowd behavior, or any other physicalbehavior of individuals located within the monitored site.

The physiological analysis module 206 is configured to analyzephysiological data from the sensor data received from the sensor array104. In the illustrative embodiment, the physiological analysis module206 analyzes the physiological data indicative of physiologicalcharacteristics of individuals in the monitored site. For example, thephysiological analysis module 206 may monitor the physiological sensordata to identify abnormal physiological characteristics. To do so, thephysiological analysis module 206 may compare the physiologicalcharacteristics to normal or expected baseline (e.g., is the individualsheart rate elevated).

As discussed above, in some embodiments, the analysis of the behavioralsensor data and the physiological sensor data is tempered or adjustedbased on context data associated with the monitored site. To do so, thecontext analysis module 208 is configured to obtain context data for themonitored site and analyze the context data for relevancy to thebehavioral and physiological analysis. In some embodiments, the threatmonitoring system 102 may store context data locally in a contextdatabase 220. Such context data may include, for example, static contextdata about the monitored site. In other embodiments, the contextanalysis module 208 may retrieve context data from one or more of theinformation systems 106. As discussed above, the context data may beembodied as any type of data usable by the threat monitoring system todetermine a context for the monitored site. For example, the contextdata may be embodied as cultural context data related to a culture ofthe individuals located within the monitored site (e.g., data definingcustomary personal distances), event or activity data, (e.g., dataidentifying an event or an activity occurring at the monitored area),temporal data (e.g., data identifying train schedules or large businessclosings, data related to the time of day or time of year), seasonaldata (e.g. data identifying expected populations based on season),past/historical behavior for particular individuals in similarcircumstances, or the like.

The context analysis module 208 may analyze the identified context datato better understand or explain monitored behavior and/or physiologicalcharacteristics. For example, the context analysis module 208 mayanalyze pedestrian traffic patterns based on train or bus schedules,crowd swelling based on rush hour timing, erratic behavior based onholidays or weekends, and/or perform other analyses on the context datato improve the analysis or understanding of the behavioral and/orphysiological data.

The threat assessment module 210 is configured to determine a threatassessment based on the behavioral analysis, the physiological analysis,and the context analysis. To do so, the threat assessment module 210 mayuse any suitable algorithm or methodology to determine the threatassessment. For example, a presence of fear-like behavior in thebehavioral sensor data coupled with a presence of fear-like response inthe physiological sensor data may be indicative of an active threat(barring contextual reasons to explain such data).

Additionally, in some embodiments, the threat assessment module 210 mayclassify the fear-based event based on size, location, and/or intensityas determined by the monitored behavior and physiological data. Suchclassification may be used in the determination of the appropriatethreat response, which is handled by a threat response module 212 of thethreat assessment module 210. To do so, the threat response module 212may communicate with the various threat response systems 108 to activatethose systems in response to an active threat. For example, the threatresponse module 212 may notify emergency response systems, controltraffic systems, notify individuals via personalized communication,generate public notifications, refocus the threat monitoring efforts, orperform some other action in response to a determination of a threat.

Referring now to FIG. 3, as discussed above, some of the sensors 150 ofthe sensor array 104 may be embodied as personal sensors 150 carried byindividuals located within the monitored site. In some embodiments,those personal sensors 150 may be embodied as sensors of personalcomputing device 300 carried by individuals. The personal computingdevices 300 may be embodied as any type of computing device such as amedical monitoring device, a biometric monitoring device, smart glasses,smart phone, smart watch or accessory, tablet computer, or othercomputing device. In such embodiments, some of the personal computingdevice 300 may include local behavioral analysis modules 204 and/orlocal physiological analysis modules 206, which may be configured toanalyze behavioral and physiological sensor data generated by a personalsensor 150 of the computing device 300 or other personal devices of theindividual. In such embodiments, the personal computing devices 300 maytransmit the behavioral analysis data and/or the physiological analysisdata to the threat monitoring system, wherein the analysis data isanalyzed by the threat assessment module 210 to determine a threatassessment. Alternatively, the behavioral analysis data and/or thephysiological analysis data may be analyzed locally on the personalcomputing device 300. It should be appreciated by incorporating thebehavioral analysis and physiological analysis into the individual'spersonal computing devices 300, the individual is provided with anincreased level of anonymity and privacy.

Referring now to FIG. 4, in use, the threat monitoring system 102 mayexecute a method 400 for determining a threat assessment. The method 400begins with block 402 in which the threat monitoring system 102 receivessensor data from the sensors 150 of the sensor array 104 located at themonitored site. As discussed above, the sensor data may includebehavioral sensor data and physiological sensor data. As such, themethod 400 branches to blocks 404 and 408 in which the behavioral sensordata and physiological sensor data is analyzed. In block 404, the threatmonitoring system 102 analyzes the behavioral sensor data indicative ofa physical behavior of individuals within the monitored site andgenerates behavioral analysis data in block 406. As discussed above, thethreat monitoring system 102 may utilize any suitable algorithm ormethodology to analyze the behavioral sensor data. In the illustrativeembodiment, the threat monitoring system 102 analyzes the behaviorsensor data to determine abnormal physical behavior of individualslocated within the monitored site. To do so, the threat monitoringsystem 102 may compare the physical behavior of monitored individuals tothe physical behavior of other individuals at the monitored locationand/or expected physical behavior. The generated behavioral analysisdata may be indicative of the determined abnormal behavior.

In block 408, the threat monitoring system 102 analyzes thephysiological sensor data indicative of physiological characteristics ofindividuals within the monitored site and generates physiologicalanalysis data in block 410. Again, the threat monitoring system 102 mayutilize any suitable algorithm or methodology to analyze thephysiological sensor data. In the illustrative embodiment, the threatmonitoring system 102 analyzes the physiological sensor data todetermine abnormal physiological characteristics of individuals locatedwithin the monitored site. To do so, the threat monitoring system 102may compare the physiological characteristics to normal or expectedbaseline values.

Subsequently, in block 412, the threat monitoring system 102 analyzescontext data relevant to the monitored area. To do so, in block 414, thethreat monitoring system 102 determines the relevant context data forthe monitored area. As discussed above, the threat monitoring system 102may store context data in the context database 220 and retrieve contextrelevant to the monitored area. The threat monitoring system 102 may useany suitable algorithm or process to determine which context data isrelevant to the monitored site. In some embodiments, context data (e.g.,temporal context data) may be relevant at different times and/or underdifferent conditions, while other context data (e.g., cultural) may berelevant at all times and under all conditions. Additionally, asdiscussed above, the threat monitoring system 102 may be configured tocontact information systems 106 to retrieve context data in block 416.

In block 418, the threat monitoring system 102 determines a threatassessment for the monitored site based on the behavioral analysis datagenerated in block 406, the physiological analysis data generated inblock 410, and the relevant context data determined in block 412. Again,as discussed above, the threat assessment module 210 may use anysuitable algorithm or methodology to determine the threat assessmentbased on such factors. In some embodiments, the threat monitoring system102 generates a threat assessment score in block 420. The threatassessment score may be used by the threat monitoring system 102 todetermine whether an active threat is present (e.g., by providing ameasureable scale against which to judge the current analysis), as wellas a measure of accountability for the undertaking of response actions,or lack thereof.

In block 422, the threat monitoring system 102 determines whether thereis an active threat based on the threat assessment determined in block418 (e.g., based on the threat score determined in block 420). If not,the method 400 loops back to block 402 in which the threat monitoringsystem 102 continues to monitor the sensor data generated by the sensorarray 104. However, if the threat monitoring system 102 determines thatthere is an active threat, the method 400 advances to block 424 in whichthe threat monitoring system 102 generates a threat response. Forexample, in block 426, the threat monitoring system 102 may communicatewith the threat response systems 108 to dispatch emergency resources tothe monitored site. In block 428, the threat monitoring system 102communicate with the threat response systems 108 to reroute traffic awayfrom the monitored site. In block 430, the threat monitoring system 102may refocus or shift the location of the monitored site (e.g., thethreat monitoring system 102 may determine the actual threat is locatedat a different location or that the active threat has relocated).Additionally, in block 432, the threat monitoring system 102 may attemptto analyze the cause the threat based on the sensor data obtained fromthe sensor array 104. For example the threat monitoring system 102 mayattempt to determine the scale of the threat, the number of actorsinvolved, the ongoing threat level, and/or any other data useful inresponding to the threat. Further, in block 434, the threat monitoringsystem 102 may generate alert notifications. As discussed above, thethreat monitoring system 102 may generate public notifications displayedor generated on public warning systems or display, as well as personalnotifications sent to personal computing devices or groups ofindividuals. For example, in some embodiments, the threat monitoringsystem 102 may generate the notifications within the monitored area toprovide some information to non-participant individuals within themonitored area. Further, the threat monitoring system 102 may contactspecific people to garner more information.

After the threat monitoring system 102 has responded to the activethreat, the method 400 loops back to block 402 in which the threatmonitoring system 102 continues monitoring the sensor data produced bythe sensor array 104. In this way, the threat monitoring system 102analyzes fear-like behavior and responses to determine the likelihood ofa threat within a monitored site and adjusts such analysis based on thecontext of the monitored site.

Although the method 400 has been described above in regard to a singlesensor array 104 and associated monitored site, it should be appreciatedthat the threat monitoring system 102 may analyze sensor data from manysensor arrays 104 in parallel. For example, in some embodiments, theconditions of one monitored site, as indicated by the sensor data, mayaffect the analysis of sensor data generated at another monitored site.

EXAMPLES

Illustrative examples of the devices, systems, and methods disclosedherein are provided below. An embodiment of the devices, systems, andmethods may include any one or more, and any combination of, theexamples described below.

Example 1 includes a threat monitoring system for determining a threatassessment at a monitored site, the threat monitoring system comprisinga sensor management module to receive sensor data from sensors of asensor array located at the monitored site, the sensor data includingbehavioral sensor data indicative of a physical behavior of individualswithin the monitored site and physiological sensor data indicative ofphysiological characteristics of individuals within the monitored site;a behavioral analysis module to analyze the behavioral sensor data togenerate behavioral analysis data; a physiological analysis module toanalyze the physiological data of the sensor data to generatephysiological analysis data; and a threat assessment module to determinea threat assessment for the monitored site based on the behavioralanalysis data and the physiological analysis data.

Example 2 includes the subject matter of Example 1, and furthercomprising a context analysis module to determine context data relatedto the monitored site, wherein to determine the threat assessmentcomprises to determine a threat assessment for the monitored site basedon the behavioral analysis data, the physiological analysis data, andthe context data.

Example 3 includes the subject matter of any of Examples 1 and 2, andwherein the context data comprises context data related to a culture ofthe individuals located within the monitored site.

Example 4 includes the subject matter of any of Examples 1-3, andwherein the context data comprises context data related to an event heldat the monitored site, an activity performed at the monitored site, thetime of day, or the time of year.

Example 5 includes the subject matter of any of Examples 1-4, andwherein to determine context data comprises to receive context data froma remote information system.

Example 6 includes the subject matter of any of Examples 1-5, andwherein to analyze the behavioral sensor data comprises to analyze thebehavioral sensor data based on the context data to generate thebehavioral analysis data.

Example 7 includes the subject matter of any of Examples 1-6, andwherein to analyze the physiological sensor data comprises to analyzethe physiological sensor data based on the context data to generate thephysiological analysis data.

Example 8 includes the subject matter of any of Examples 1-7, andwherein to analyze the behavioral sensor data comprises to compare aphysical behavior of an individual located within the monitored site toother individuals located within the monitored site to detect abnormalphysical behavior.

Example 9 includes the subject matter of any of Examples 1-8, andwherein to detect the abnormal physical behavior comprises to detect thewearing of abnormal clothing by the individual relative to the clothingworn by the other individuals located within the monitored site.

Example 10 includes the subject matter of any of Examples 1-9, andwherein to detect the abnormal physical behavior comprises to detect anabnormal physical proximity of the individual to another individualwithin the monitored site relative to proximities of other individualswith each other.

Example 11 includes the subject matter of any of Examples 1-10, andwherein to detect the abnormal physical behavior comprises to detect anabnormal movement of the individual relative to the movement of theother individuals located within the monitored site.

Example 12 includes the subject matter of any of Examples 1-11, andwherein to analyze the physiological sensor data comprises to compare aphysiological characteristic of an individual located within themonitored site to an expected normal value to detect an abnormalphysical characteristic of the individual.

Example 13 includes the subject matter of any of Examples 1-12, andwherein the physiological characteristic comprises at least one of aheart rate, a galvanic skin response, or a biochemical reaction.

Example 14 includes the subject matter of any of Examples 1-13, andwherein the threat assessment module is further to determine thepresence of an active threat based on the threat assessment; andgenerate a threat response in response to a determination of an activethreat.

Example 15 includes the subject matter of any of Examples 1-14, andwherein to generate the threat response comprises to (i) dispatchemergency resources to the monitored site, (ii) reroute traffic awayfrom the monitored site, (iii) generate a notification of the activethreat, or (iv) commence the monitoring of a different monitored site.

Example 16 includes the subject matter of any of Examples 1-15, andwherein the sensor data comprises behavioral sensor data from abehavioral sensor and physiological sensor data from a physiologicalsensor.

Example 17 includes the subject matter of any of Examples 1-16, andwherein at least one of the behavioral sensor or the physiologicalsensor is a stationary sensor located at the monitored site.

Example 18 includes the subject matter of any of Examples 1-17, andwherein the stationary sensor comprises at least one of a camera sensor,an audio sensor, a motion sensor, a communication sensor, or a chemicalsensor.

Example 19 includes the subject matter of any of Examples 1-18, and,wherein at least one of the behavioral sensor or the physiologicalsensor is a personal sensor carried on the person of an individuallocated within the monitored site.

Example 20 includes the subject matter of any of Examples 1-19, andwherein the personal sensor a camera, a head-worn video device, a motionsensor, an audio sensor, a proximity sensor, a pedometer, a heart ratesensor, a galvanic skin response sensor, or a breathing sensor carriedby the individual.

Example 21 includes a method for determining a threat assessment at amonitored site, the method comprising receiving sensor data from sensorsof a sensor array located at the monitored site, the sensor dataincluding behavioral sensor data indicative of a physical behavior ofindividuals within the monitored site and physiological sensor dataindicative of physiological characteristics of individuals within themonitored site; analyzing the behavioral sensor data to generatebehavioral analysis data; analyzing the physiological data of the sensordata to generate physiological analysis data; and determining a threatassessment for the monitored site based on the behavioral analysis dataand the physiological analysis data.

Example 22 includes the subject matter of Example 21, and furtherincluding determining context data related to the monitored site,wherein determining the threat assessment comprises determining a threatassessment for the monitored site based on the behavioral analysis data,the physiological analysis data, and the context data.

Example 23 includes the subject matter of any of Examples 21 and 22, andwherein determining context data comprises determining context datarelated to a culture of the individuals located within the monitoredsite.

Example 24 includes the subject matter of any of Examples 21-23, andwherein determining context data comprises determining context datarelated to an event held at the monitored site, an activity performed atthe monitored site, the time of day, or the time of year.

Example 25 includes the subject matter of any of Examples 21-24, andwherein determining context data comprises retrieving context data froma remote information system.

Example 26 includes the subject matter of any of Examples 21-25, andwherein analyzing the behavioral sensor data comprises analyzing thebehavioral sensor data based on the context data to generate thebehavioral analysis data.

Example 27 includes the subject matter of any of Examples 21-26, andwherein analyzing the physiological sensor data comprises analyzing thephysiological sensor data based on the context data to generate thephysiological analysis data.

Example 28 includes the subject matter of any of Examples 21-27, andwherein analyzing the behavioral sensor data comprises comparing aphysical behavior of an individual located within the monitored site toother individuals located within the monitored site to detect abnormalphysical behavior.

Example 29 includes the subject matter of any of Examples 21-28, andwherein to detect the abnormal physical behavior comprises to detect thewearing of abnormal clothing by the individual relative to the clothingworn by the other individuals located within the monitored site.

Example 30 includes the subject matter of any of Examples 21-29, andwherein to detect the abnormal physical behavior comprises to detect anabnormal physical proximity of the individual to another individualwithin the monitored site relative to proximities of other individualswith each other.

Example 31 includes the subject matter of any of Examples 21-30, andwherein to detect the abnormal physical behavior comprises to detect anabnormal movement of the individual relative to the movement of theother individuals located within the monitored site.

Example 32 includes the subject matter of any of Examples 21-31, andwherein analyzing the physiological sensor data comprises comparing aphysiological characteristic of an individual located within themonitored site to an expected normal value to detect an abnormalphysical characteristic of the individual.

Example 33 includes the subject matter of any of Examples 21-32, andwherein the physiological characteristic comprises at least one of aheart rate, a galvanic skin response, or a biochemical reaction.

Example 34 includes the subject matter of any of Examples 21-33, andfurther including determining the presence of an active threat based onthe threat assessment; and generating a threat response in response to adetermination of an active threat.

Example 35 includes the subject matter of any of Examples 21-34, andwherein generating the threat response comprises at least one ofdispatch emergency resources to the monitored site, rerouting trafficaway from the monitored site, generating a notification of the activethreat, or commencing the monitoring of a different monitored site.

Example 36 includes the subject matter of any of Examples 21-35, andwherein receiving sensor data comprises receiving behavioral sensor datafrom a behavioral sensor and receiving physiological sensor data from aphysiological sensor.

Example 37 includes the subject matter of any of Examples 21-36, andwherein at least one of the behavioral sensor or the physiologicalsensor is a stationary sensor located at the monitored site.

Example 38 includes the subject matter of any of Examples 21-37, andwherein the stationary sensor comprises at least one of a camera sensor,an audio sensor, a motion sensor, a communication sensor, or a chemicalsensor.

Example 39 includes the subject matter of any of Examples 21-38, andwherein at least one of the behavioral sensor or the physiologicalsensor is a personal sensor carried on the person of an individuallocated within the monitored site.

Example 40 includes the subject matter of any of Examples 21-39, andwherein the personal sensor a camera, a head-worn video device, a motionsensor, an audio sensor, a proximity sensor, a pedometer, a heart ratesensor, a galvanic skin response sensor, or a breathing sensor carriedby the individual.

Example 41 includes one or more computer-readable storage mediacomprising a plurality of instructions stored thereon that, in responseto execution, cause a threat monitoring system to perform the method ofany of Examples 21-40.

Example 42 includes a threat monitoring system for determining a threatassessment at a monitored site, the threat monitoring system comprisingmeans for performing the method of any of Examples 21-40.

The invention claimed is:
 1. A threat monitoring compute devicecomprising: a communication circuit; one or more processors; and one ormore memory devices that include a plurality of instructions that, whenexecuted by the one or more processors, cause the threat monitoringcompute device to: receive, by the communication circuit, sensor datafrom one or more sensors of a sensor array located at the monitoredsite, wherein the sensor data is indicative of a level of fear presentlyfelt by one or more individuals located within the monitored site andwherein the sensor data includes behavioral sensor data indicative of aphysical behavior of a first individual of the one or more individuals;analyze the sensor data based on context data related to the monitoredsite to determine whether a threat is presently occurring at themonitored site, wherein the analysis of the sensor data includes acomparison of a behavior of the first individual indicated by thebehavioral sensor data to a behavior of the one or more individualsother than the first individual to determine whether the firstindividual is displaying abnormal behavior; and analyze, in response toa determination that a threat is presently occurring at the monitoredsite and based on the sensor data, a cause of the threat.
 2. The threatmonitoring compute device of claim 1, wherein to: analyze the sensordata comprises to analyze the behavior sensor data to determine whetherthe first individual is displaying abnormal behavior based on thecontext data.
 3. The threat monitoring compute device of claim 1,wherein to: receive the sensor data from the one or more sensors of thesensor array comprises to receive physiological sensor data indicativeof a physiological characteristic of the first individual, and analyzethe sensor data comprises to analyze the physiological sensor data todetermine whether the first individual is experiencing an abnormalphysiological response based on the context data.
 4. The threatmonitoring compute device of claim 3, wherein to analyze thephysiological sensor data comprises to compare a physiological responseof the first individual indicated by the physiological sensor data tophysiological responses of other individuals presently located in themonitored site.
 5. The threat monitoring compute device of claim 1,wherein to analyze the sensor data comprises to: analyze the sensor todetermine an initial threat assessment for the monitored site, modifythe initial threat assessment based on the context data, and determinewhether a threat is presently occurring at the monitored site based onthe modified initial threat assessment.
 6. The threat monitoring computedevice of claim 1, wherein to receive the sensor data comprises toreceive sensor data from a personal compute device carried on the personof an individual located within the monitored site, and wherein theplurality of instructions, when executed by the one or more processors,further cause the threat monitoring compute device to transmit an alertnotification to the personal compute device in response to adetermination that a threat is presently occurring at the monitoredsite.
 7. The threat monitoring compute device of claim 1, wherein thecontext data defines an expected behavior or physiological response ofindividuals presently located within the monitored site.
 8. A methodcomprising: receiving, by the communication circuit of a threatmonitoring compute device, sensor data from one or more sensors of asensor array located at the monitored site, wherein the sensor data isindicative of a level of fear presently felt by one or more individualslocated within the monitored site and wherein the sensor data includesbehavioral sensor data indicative of a physical behavior of a firstindividual of the one or more individuals; analyzing, by the threatmonitoring compute device, the sensor data based on context data relatedto the monitored site to determine whether a threat is presentlyoccurring at the monitored site, wherein the analysis of the sensor dataincludes a comparison of a behavior of the first individual indicated bythe behavioral sensor data to a behavior of the one or more individualsother than the first individual to determine whether the firstindividual is displaying abnormal behavior; and analyzing, in responseto a determination that a threat is presently occurring at the monitoredsite and based on the sensor data, a cause of the threat.
 9. The methodof claim 8, wherein: analyzing the sensor data comprises analyzing thebehavior sensor data to determine whether the first individual isdisplaying abnormal behavior based on the context data.
 10. The methodof claim 8, wherein: receiving the sensor data from the one or moresensors of the sensor array comprises receiving physiological sensordata indicative of a physiological characteristic of the firstindividual, and analyzing the sensor data comprises analyzing thephysiological sensor data to determine whether the first individual isexperiencing an abnormal physiological response based on the contextdata.
 11. The method of claim 10, wherein analyzing the physiologicalsensor data comprises comparing a physiological response of the firstindividual indicated by the physiological sensor data to physiologicalresponses of other individuals presently located in the monitored site.12. The method of claim 8, wherein analyzing the sensor data comprises:analyzing the sensor to determine an initial threat assessment for themonitored site, modifying the initial threat assessment based on thecontext data, and determining whether a threat is presently occurring atthe monitored site based on the modified initial threat assessment. 13.The method of claim 8, wherein receiving the sensor data comprisesreceiving sensor data from a personal compute device carried on theperson of an individual located within the monitored site, and furthercomprising transmitting an alert notification to the personal computedevice in response to a determination that a threat is presentlyoccurring at the monitored site.
 14. The method of claim 8, wherein thecontext data defines an expected behavior or physiological response ofindividuals presently located within the monitored site.
 15. One or morenon-transitory machine-readable storage media comprising a plurality ofinstructions stored thereon that, when executed, causes a threatmonitoring compute device to: receive sensor data from one or moresensors of a sensor array located at the monitored site, wherein thesensor data is indicative of a level of fear presently felt by one ormore individuals located within the monitored site and wherein thesensor data includes behavioral sensor data indicative of a physicalbehavior of a first individual of the one or more individuals; analyzethe sensor data based on context data related to the monitored site todetermine whether a threat is presently occurring at the monitored site,wherein the analysis of the sensor data includes a comparison of abehavior of the first individual indicated by the behavioral sensor datato a behavior of the one or more individuals other than the firstindividual to determine whether the first individual is displayingabnormal behavior; and analyze, in response to a determination that athreat is presently occurring at the monitored site and based on thesensor data, a cause of the threat.
 16. The one or more non-transitorymachine-readable storage media of claim 15, wherein to: analyze thesensor data comprises to analyze the behavior sensor data to determinewhether the first individual is displaying abnormal behavior based onthe context data.
 17. The one or more non-transitory machine-readablestorage media of claim 15, wherein to: receive the sensor data from theone or more sensors of the sensor array comprises to receivephysiological sensor data indicative of a physiological characteristicof the first individual, and analyze the sensor data comprises toanalyze the physiological sensor data to determine whether the firstindividual is experiencing an abnormal physiological response based onthe context data.
 18. The one or more non-transitory machine-readablestorage media of claim 17, wherein to analyze the physiological sensordata comprises to compare a physiological response of the firstindividual indicated by the physiological sensor data to physiologicalresponses of other individuals presently located in the monitored site.19. The one or more non-transitory machine-readable storage media ofclaim 15, wherein to analyze the sensor data comprises to: analyze thesensor to determine an initial threat assessment for the monitored site,modify the initial threat assessment based on the context data, anddetermine whether a threat is presently occurring at the monitored sitebased on the modified initial threat assessment.
 20. The one or morenon-transitory machine-readable storage media of claim 15, wherein toreceive the sensor data comprises to receive sensor data from a personalcompute device carried on the person of an individual located within themonitored site, and wherein the plurality of instructions, when executedby the one or more processors, further cause the threat monitoringcompute device to transmit an alert notification to the personal computedevice in response to a determination that a threat is presentlyoccurring at the monitored site.
 21. The one or more non-transitorymachine-readable storage media of claim 15, wherein the context datadefines an expected behavior or physiological response of individualspresently located within the monitored site.